Research On Nonlinear Correction And Dynamic Compensation Of Sensors

Sensor is the core component in the measuring systems, and its accuracy play a decisive role in the performance of measuring systems. Moreover, the key to enhance the performance of sensors lies in correcting or compensating their static characteristics (nonlinear) and dynamic characteristics, which has already become an important subject researched both at home and abroad at present time. The main task of this dissertation is the nonlinear correction and dynamic compensation of sensors. A new nonlinear correction method is proposed, and the first choice of dynamic compensation methods under different environment is given by comparison.This dissertation proposes a new type of nonlinear correction method after briefly introducing the traditional methods. Firstly, the feasibility of this method is deduced theoretically and the model is established. This method can reduce the system's complexity comparing with the traditional ones. Then the measuring system using two distance sensors is set up to acquire data through the computer. The nonlinear correction model with two inputs and one output can be established by the neural network because of its nonlinear approximation, self-learning and fault-tolerant abilities. The system linked this model has a good linear input-output characteristic. RPE (recursive prediction error) and RBF (Radial Basis...